r - How Do I Calculate Proportions Of Data Subsets? -

i've got code below need with. i'm asking data science coursera class "are americans financial satisfaction affected previous year's annual s&p500 gain/loss?". i'm trying plot graph amount of observations either satisfied or more or less satisfied, against entire population (a proportion) y axis, , "percentchange" x-axis. posted entire code further down, in case necessary understand i'm trying do. of these observations in same table "finalresults" , listed under variable column categorical, named "financialsatisfaction". i'm not sure go here, big problem i'm having how calculate proportions based on "percentchange" in final results table. right below had tried, way off. need filter satisfaction proportions year, x-axis each year's percentage change. appreciated, near knowledgeable enough r figure out.

satisfied <- subset(finalresults, financialsatisfaction == "satisfied") moreorless <- subset(finalresults, financialsatisfaction == "more or less") notatall <- subset(finalresults, financialsatisfaction == "not @ all")  myproportion = (satisfied + moreorless) / 29205 

full code:

require(quandl) require(lubridate) require(zoo) require(xts)  mygss <- load(url("http://bit.ly/dasi_gss_data"))  year <- gss$year finsat <- gss$satfin  relativetable <- data.frame(year, finsat) relativetable <- subset(relativetable, year > "1988" & !is.na(finsat))   spreturns <- quandl("sandp/annrets", trim_start="1970-01-11",                      trim_end="2012-12-31", authcode="nwy3a_gmd7tss9fvirxt",                      collapse="annual")  percentchange <- spreturns$"total return change"  spreturns$"year ending" <- format((spreturns$"year ending"), "%y") spreturns$"year ending" <- as.numeric(spreturns$"year ending") spreturns$"year ending" <- spreturns[,1] + 1 #the following year  combined <- merge(relativetable, spreturns, by.x = "year", by.y = "year ending") names(combined)[6] <- "percentchange"  finalresults <- data.frame(combined$year, combined$finsat, combined$percentchange) names(finalresults)[1] <- "year" names(finalresults)[2] <- "financialsatisfaction" names(finalresults)[3] <- "percentchange" finalresults$percentchange <- finalresults$percentchange * 100  satisfied <- subset(finalresults, financialsatisfaction == "satisfied") moreorless <- subset(finalresults, financialsatisfaction == "more or less") notatall <- subset(finalresults, financialsatisfaction == "not @ all")  myproportion <- (satisfied + moreorless) / 29205 

in code,

myproportion = (satisfied + moreorless) / 29205 

satisfied , moreorless data.frames, result df; want like

myproporition <- mean(finalresults$financialsatisfaction == "satisfied" | finalresults$financialsatisfaction == "more or less")